Analysis of long image sequence for structure and motion estimation
Ghwan-Lu Tseng, Arun K. Sood · IEEE Transactions on Systems Man and Cybernetics · 1989
A motion parameter estimation technique is presented for image sequence analysis of several frames. A dynamic scene model is developed in which image sequences are processed as a temporally correlated complex. Using this model, measurement of the position of the object in a set of consecutive frames permits the estimation of motion as a function of time. The measurement consists of a sequence of image coordinates of three or more feature correspondence points in each frame. The motion sequence is represented as a discrete-time time-varying system. An iterative mathematical parameter estimation technique is used to minimize the projection error. The fundamental concept of this analysis is based on optimal control theory. Motion parameter estimates are extracted from the sequence of image correspondence by modeling the motion dynamics using motion transformation and viewing projection. Object positions are estimated by iteratively refining the parameters by small perturbations. This methodology is suitable for processing a long sequence in situations where a high rate of imagery is available. Results are presented for generalized rigid-body motion of synthesized images and real images.>